Artificial Intelligence Questions & Answers Answers – Uninformed Search Search Strategy This set of Artificial Intelligence MCQ focuses on “Uninformed Search Strategy”. 1. Which search strategy is also called as lind search! a" Uninformed search " Informed search c" Sim#le refle$ search d" All of the mentioned %ie& Ans&er Ans&er'a ($#lanation'In lind search) We can search the states &ithout ha*ing any additional information. So uninformed search method is lind search. +. ,o& many ty#es are a*ailale in uninformed search method! a" " c" d" /0 %ie& Ans&er Ans&er'c ($#lanation'The fi*e ty#es of uninformed search method are readth2first) Uniform2cost) 3e#th2first) 3e#th2limited and idirectional search. -. Which search is im#lemented &ith an em#ty first2in2first2out 4ueue! a" 3e#th2first search " readth2first search c" idirectional search d" 5one of the mentioned %ie& Ans&er Ans&er' ($#lanation'ecause of 6I67 4ueue) it &ill assure that the nodes that are *isited first &ill e e$#anaded first. . When is readth2first search is o#timal! a" When there is less numer of nodes " When all ste# costs are e4ual c" When all ste# costs are une4ual d" oth a 8 c %ie& Ans&er Ans&er' ($#lanation'ecause it al&ays e$#ands the shallo&est une$#anded node.
/. ,o& many successors are generated in ac9trac9ing search! a" 1 " + c" d" %ie& Ans&er Ans&er'a ($#lanation'(ach #artially e$#anded node rememers &hich successor to generate ne$t ecause of these condition) it uses less memory. 0. What is the s#ace com#le$ity of 3e#th2first search! a" 7:" " 7:l" c" 7:m" d" 7:m" %ie& Ans&er Ans&er'd ($#lanation'7:m" is the s#ace com#le$ity &here is the ranching factor andm is the ma$imum de#th of the search tree. ;. ,o& many #arts does a #rolem consists of! a" 1 " + c" d" %ie& Ans&er Ans&er'd ($#lanation'The four #arts of the #rolem are intial state) set of actions) goal test and #ath cost. . Which search im#lements stac9 o#eration for searching the states! a" 3e#th2limited search " 3e#th2first search c" readth2first search d" 5one of the mentioned %ie& Ans&er Ans&er' ($#lanation'It im#lements stac9 o#eration ecause it al&ays e$#ands the dee#est node in the current tree.
Artificial Intelligence Questions & Answers Answers – Informed Search Search Strategy This set of Artificial Intelligence MCQ focuses on “Informed Search Strategy”. 1. What is the other name of informed search strategy! a" Sim#le search " ,euristic search c" 7nline search d" 5one of the mentioned %ie& Ans&er Ans&er' ($#lanation'A 9ey #oint of informed search strategy is heuristic function) So it is called as heuristic function. +. ,o& many ty#es of informed search method are in artificial intelligence! a" 1 " + c" d" %ie& Ans&er Ans&er'd ($#lanation'The four ty#es of informed search method are est2first search) ?reedy est2first search) A@ search and memory ounded heuristic search. -. Which search uses the #rolem s#ecific 9no&ledge eyond the definition of the #rolem!
a" Informed search " 3e#th2first search c" readth2first search d" Uninformed search %ie& Ans&er Ans&er'a ($#lanation'Informed search can sol*e the #rolem eyond the function definition) So does it can find the solution more efficiently. . Which function &ill select the lo&est e$#ansion node atfirst for e*aluation! a" ?reedy est2first search " est2first search c" oth a 8 d" 5one of the mentioned %ie& Ans&er Ans&er' ($#lanation'The lo&est e$#ansion node is selected ecause the e*aluation measures distance to the goal. /. What is the heuristic function of greedy est2first search! a" f:n" B h:n" " f:n" h:n" c" f:n" B h:n" d" f:n" D h:n" %ie& Ans&er Ans&er'c ($#lanation'5one 0. Which search uses only the linear s#ace for searching! a" est2first search " Eecursi*e est2first search c" 3e#th2first search d" 5one of the mentioned %ie& Ans&er Ans&er' ($#lanation'Eecursi*e est2first search &ill mimic the o#eration of standard est2first search) ut using only the linear s#ace. ;. Which method is used to search etter y learning! a" est2first search " 3e#th2first search c" Metale*el state s#ace d" 5one of the mentioned %ie& Ans&er
Ans&er'c ($#lanation'This search strategy &ill hel#s to #rolem sol*ing efficiency y using learning.
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